OpenRaiser/Intern-Atlas huggingface dataset:
Coding and Decoding Schemes for MSE and Image Transmission
Venue: arXiv cs.IT 2014
Year: 2014

In this work we explore possibilities for coding and decoding tailor-made for mean squared error evaluation of error in contexts such as image transmission. To do so, we introduce a loss function that expresses the overall performance of a coding and decoding scheme for discrete channels and that exchanges the usual goal of minimizing the error probability to that of minimizing the expected loss. In this environment we explore the possibilities of using ordered decoders to create a message-wise unequal error protection (UEP), where the most valuable information is protected by placing in its proximity information words that differ by a small valued error. We give explicit examples, using scale-of-gray images, including small-scale performance analysis and visual simulations for the BSMC.
Multilinear Principal Component Analysis Network for Tensor Object Classification
Venue: arXiv cs.CV 2014
Year: 2014

The recently proposed principal component analysis network (PCANet) has been proved high performance for visual content classification. In this letter, we develop a tensorial extension of PCANet, namely, multilinear principal analysis component network (MPCANet), for tensor object classification. Compared to PCANet, the proposed MPCANet uses the spatial structure and the relationship between each dimension of tensor objects much more efficiently. Experiments were conducted on different visual content datasets including UCF sports action video sequences database and UCF11 database. The experimental results have revealed that the proposed MPCANet achieves higher classification accuracy than PCANet for tensor object classification.
MultiQueues: Simpler, Faster, and Better Relaxed Concurrent Priority Queues
Venue: arXiv cs.DS 2014
Year: 2014

Priority queues with parallel access are an attractive data structure for applications like prioritized online scheduling, discrete event simulation, or branch-and-bound. However, a classical priority queue constitutes a severe bottleneck in this context, leading to very small throughput. Hence, there has been significant interest in concurrent priority queues with a somewhat relaxed semantics where deleted elements only need to be close to the minimum. In this paper we present a very simple approach based on multiple sequential priority queues. It turns out to outperform previous more complicated data structures while at the same time improving the quality of the returned elements.
An Open Distributed Architecture for Flexible Hybrid Assembly Systems: A Model Driven Engineering Approach
Venue: arXiv cs.SE 2014
Year: 2014

Assembly systems constitute one of the most important fields in today industry. In this paper we propose an open distributed architecture for the engineering of evolvable flexible hybrid assembly systems. The proposed architecture is based on the model driven development paradigm. Models are used to represent structure and behavior and a domain specific engineering tool is defined to facilitate the assembly system engineer in the engineering process of the assembly system. Specific meta models are defined to capture domain knowledge to guide the engineer in the construction of the models required to construct the assembly system. This work is a specialization of our previous work that defined a SOA based framework for embedded industrial automation systems. It adapts and extends, in the assembly systems domain, the 3+1 SysML-view model architecture defined for the engineering of mechatronics Manufacturing systems. The proposed architecture can be used to develop a framework for evolvable flexible and reconfigurable assembly systems that would exploit the benefits the Cyber Physical paradigm utilizing web technologies, the IoT, the Cloud computing and Big Data.
Bibliometric Indicators for Publishers: Data processing, indicators and interpretation
Venue: arXiv cs.DL 2014
Year: 2014

Here we describe the Bibliometric Indicators for Publishers Project, an initiative undertaken by EC3Metrics SL for the analysis and development of indicators based on books and book chapters. Its goal is to study and analyze the publication and citation patterns of books and book chapters considering academic publishers as the unit of analysis. It aims at developing new methodologies and indicators that can better capture and define the research impact of publishers. It is an on-going project in which data sources and indicators are tested. We consider academic publishers as an analogy of journals, focusing on them as the unit of analysis. In this working paper we present the http://bipublishers.es website where all findings derived from the project are displayed. We describe the data retrieval and normalization process and we show the main results. A total 482,470 records have been retrieved and processed, identifying 342 publishers from which 254 have been analyzed. Then six indicators have been calculated for each publisher for four fields and 38 disciplines and displayed.
The Value of Knowing Your Enemy
Venue: arXiv cs.GT 2014
Year: 2014

Many auction settings implicitly or explicitly require that bidders are treated equally ex-ante. This may be because discrimination is philosophically or legally impermissible, or because it is practically difficult to implement or impossible to enforce. We study so-called {\em anonymous} auctions to understand the revenue tradeoffs and to develop simple anonymous auctions that are approximately optimal. We consider digital goods settings and show that the optimal anonymous, dominant strategy incentive compatible auction has an intuitive structure --- imagine that bidders are randomly permuted before the auction, then infer a posterior belief about bidder i's valuation from the values of other bidders and set a posted price that maximizes revenue given this posterior. We prove that no anonymous mechanism can guarantee an approximation better than O(n) to the optimal revenue in the worst case (or O(log n) for regular distributions) and that even posted price mechanisms match those guarantees. Understanding that the real power of anonymous mechanisms comes when the auctioneer can infer the bidder identities accurately, we show a tight O(k) approximation guarantee when each bidder can be confused with at most k "higher types". Moreover, we introduce a simple mechanism based on n target prices that is asymptotically optimal and build on this mechanism to extend our results to m-unit auctions and sponsored search.
Sparse Phase Retrieval from Short-Time Fourier Measurements
Venue: arXiv cs.IT 2014
Year: 2014

We consider the classical 1D phase retrieval problem. In order to overcome the difficulties associated with phase retrieval from measurements of the Fourier magnitude, we treat recovery from the magnitude of the short-time Fourier transform (STFT). We first show that the redundancy offered by the STFT enables unique recovery for arbitrary nonvanishing inputs, under mild conditions. An efficient algorithm for recovery of a sparse input from the STFT magnitude is then suggested, based on an adaptation of the recently proposed GESPAR algorithm. We demonstrate through simulations that using the STFT leads to improved performance over recovery from the oversampled Fourier magnitude with the same number of measurements.
Spin Wave Neuroanalog of von Neumann's Microwave Computer
Venue: arXiv cs.ET 2014
Year: 2014

Frequency and phase of neural activity play important roles in the behaving brain. The emerging understanding of these roles has been informed by the design of analog devices that have been important to neuroscience, among them the neuroanalog computer developed by O. Schmitt in the 1930's. In the 1950's, J. von Neumann, in a search for high performance computing using microwaves, invented a logic machine based on similar devices, that can perform logic functions including binary arithmetic. Described here is a novel embodiment of his machine using nano-magnetics. The embodiment is based on properties of ferromagnetic thin films that are governed by a nonlinear Schrodinger equation for magnetization in a film. Electrical currents through point contacts on a film create spin torque nano oscillators (STNO) that define the oscillator elements of the system. These oscillators may communicate through directed graphs of electrical connections or by radiation in the form of spin waves. It is shown here how to construct a logic machine using STNO, that this machine can perform several computations simultaneously using multiplexing of inputs, that this system can evaluate iterated logic functions, and that spin waves can communicate frequency, phase and binary information. Neural tissue and the Schmitt, von Neumann and STNO devices share a common bifurcation structure, although these systems operate on vastly different space and time scales. This suggests that neural circuits may be capable of computational functionality described here.
Tensor Transpose and Its Properties
Venue: arXiv cs.NA 2014
Year: 2014

Tensor transpose is a higher order generalization of matrix transpose. In this paper, we use permutations and symmetry group to define? the tensor transpose. Then we discuss the classification and composition of tensor transposes. Properties of tensor transpose are studied in relation to tensor multiplication, tensor eigenvalues, tensor decompositions and tensor rank.
Convolutional Neural Network-based Place Recognition
Venue: arXiv cs.CV 2014
Year: 2014

Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.
The edit distance for Reeb graphs of surfaces
Venue: arXiv cs.CG 2014
Year: 2014

Reeb graphs are structural descriptors that capture shape properties of a topological space from the perspective of a chosen function. In this work we define a combinatorial metric for Reeb graphs of orientable surfaces in terms of the cost necessary to transform one graph into another by edit operations. The main contributions of this paper are the stability property and the optimality of this edit distance. More precisely, the stability result states that changes in the functions, measured by the maximum norm, imply not greater changes in the corresponding Reeb graphs, measured by the edit distance. The optimality result states that our edit distance discriminates Reeb graphs better than any other metric for Reeb graphs of surfaces satisfying the stability property.
Large System Analysis for Amplify & Forward SIMO Multiple Access Channel with Ill-conditioned Second Hop
Venue: arXiv cs.IT 2014
Year: 2014

Relaying has been extensively studied during the last decades and has found numerous applications in wireless communications. The simplest relaying method, namely amplify and forward, has shown potential in MIMO multiple access systems, when Gaussian fading channels are assumed for both hops. However, in some cases ill conditioned channels may appear on the second hop. For example, this impairment could affect cooperative BS systems with microwave link backhauling, which involve strong line of sight channels with insufficient scattering. In this paper, we consider a large system analysis of such as model focusing on both optimal joint decoding and joint MMSE filtering receivers. Analytical methods based on free probability are presented for calculating the ergodic throughput, the MMSE error and the average SINR. Furthermore, the performance degradation of the system throughput is evaluated considering second hop impairments such as ill-conditioning and rank deficiency, while high- and low-SNR limits are calculated for the considered performance metrics. Finally, the cooperative BS system is compared to a conventional channel resource division strategy and suitable operating points are proposed.
A Parameterized Base Station Power Model
Venue: arXiv cs.IT 2014
Year: 2014

Power models are needed to assess the power consumption of cellular Base Station (BS) on an abstract level. Currently available models are either too simplified to cover necessary aspects or overly complex. We provide a parameterized linear power model which covers the individual aspects of a BS which are relevant for a power consumption analysis, especially the transmission bandwidth and the number of radio chains. Details reflecting the underlying architecture are abstracted in favor of simplicity and applicability. We identify current power-saving techniques of cellular networks for which this model can be used. Furthermore, the parameter set of typical commercial BS is provided and compared to the underlying complex model. The complex model is well approximated while only using a fraction of the input parameters.
Space proof complexity for random $3$-CNFs via a $(2-ε)$-Hall's Theorem
Venue: arXiv cs.CC 2014
Year: 2014

We investigate the space complexity of refuting $3$-CNFs in Resolution and algebraic systems. No lower bound for refuting any family of $3$-CNFs was previously known for the total space in resolution or for the monomial space in algebraic systems. We prove that every Polynomial Calculus with Resolution refutation of a random $3$-CNF $ϕ$ in $n$ variables requires, with high probability, $Ω(n/\log n)$ distinct monomials to be kept simultaneously in memory. The same construction also proves that every Resolution refutation $ϕ$ requires, with high probability, $Ω(n/\log n)$ clauses each of width $Ω(n/\log n)$ to be kept at the same time in memory. This gives a $Ω(n^2/\log^2 n)$ lower bound for the total space needed in Resolution to refute $ϕ$. The main technical innovation is a variant of Hall's theorem. We show that in bipartite graphs $G$ with bipartition $(L,R)$ and left-degree at most 3, $L$ can be covered by certain families of disjoint paths, called $(2,4)$-matchings, provided that $L$ expands in $R$ by a factor of $(2-ε)$, for $ε< \frac{1}{23}$.
A filtering technique for Markov chains with applications to spectral embedding
Venue: arXiv cs.DM 2014
Year: 2014

Spectral methods have proven to be a highly effective tool in understanding the intrinsic geometry of a high-dimensional data set $\left\{x_i \right\}_{i=1}^{n} \subset \mathbb{R}^d$. The key ingredient is the construction of a Markov chain on the set, where transition probabilities depend on the distance between elements, for example where for every $1 \leq j \leq n$ the probability of going from $x_j$ to $x_i$ is proportional to $$ p_{ij} \sim \exp \left( -\frac{1}{\varepsilon}\|x_i -x_j\|^2_{\ell^2(\mathbb{R}^d)}\right) \qquad \mbox{where}~\varepsilon>0~\mbox{is a free parameter}.$$ We propose a method which increases the self-consistency of such Markov chains before spectral methods are applied. Instead of directly using a Markov transition matrix $P$, we set $p_{ii} = 0$ and rescale, thereby obtaining a transition matrix $P^*$ modeling a non-lazy random walk. We then create a new transition matrix $Q = (q_{ij})_{i,j=1}^{n}$ by demanding that for fixed $j$ the quantity $q_{ij}$ be proportional to $$ q_{ij} \sim \min((P^*)_{ij}, ((P^*)^2)_{ij}, \dots, ((P^*)^k)_{ij}) \qquad \mbox{where usually}~ k=2.$$ We consider several classical data sets, show that this simple method can increase the efficiency of spectral methods and prove that it can correct randomly introduced errors in the kernel.
Wireless-Delimited Secure Zones with Encrypted Attribute-Based Broadcast for Safe Firearms
Venue: arXiv cs.CR 2014
Year: 2014

This work presents an application of the highly expressive Attribute-Based Encryption to implement wireless-delimited Secure Zones for firearms. Within these zones, radio-transmitted local policies based on attributes of the consumer and the firearm are received by embedded hardware in the firearms, which then advises the consumer about safe operations. The Secure Zones utilize Attribute-Based Encryption to encode the policies and consumer or user attributes, and providing privacy and security through it cryptography. We describe a holistic approach to evolving the firearm to a cyber-physical system to aid in augmenting safety. We introduce a conceptual model for a firearm equipped with sensors and a context-aware software agent. Based on the information from the sensors, the agent can access the context and inform the consumer of potential unsafe operations. To support Secure Zones and the cyber-physical firearm model, we propose a Key Infrastructure Scheme for key generation, distribution, and management, and a Context-Aware Software Agent Framework for Firearms.
Conditional Generative Adversarial Nets
Venue: arXiv cs.LG 2014
Year: 2014

Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adversarial nets, which can be constructed by simply feeding the data, y, we wish to condition on to both the generator and discriminator. We show that this model can generate MNIST digits conditioned on class labels. We also illustrate how this model could be used to learn a multi-modal model, and provide preliminary examples of an application to image tagging in which we demonstrate how this approach can generate descriptive tags which are not part of training labels.
Is there any measurable benefit in publishing preprints in the arXiv section Quantitative Biology?
Venue: arXiv cs.DL 2014
Year: 2014

A public preprint server such as arXiv allows authors to publish their manuscripts before submitting them to journals for peer review. It offers the chance to establish priority by making the results available upon completion. This article presents the arXiv section Quantitative Biology and investigates the advantages of preprint publications in terms of reception, which can be measured by means of citations. This paper focuses on the publication and citation delay, citation counts and the authors publishing their e-prints on arXiv. Moreover, the paper discusses the benefit for scientists as well as publishers. The results that are based on 12 selected journals show that submitting preprints to arXiv has become more common in the past few years, but the number of papers submitted to Quantitative Biology is still small and represents only a fraction of the total research output in biology. An immense advantage of arXiv is to overcome the long publication delay resulting from peer review. Although preprints are visible prior to the officially published articles, a significant citation advantage was only found for the Journal of Theoretical Biology.
Power-Law Graph Cuts
Venue: arXiv cs.CV 2014
Year: 2014

Algorithms based on spectral graph cut objectives such as normalized cuts, ratio cuts and ratio association have become popular in recent years because they are widely applicable and simple to implement via standard eigenvector computations. Despite strong performance for a number of clustering tasks, spectral graph cut algorithms still suffer from several limitations: first, they require the number of clusters to be known in advance, but this information is often unknown a priori; second, they tend to produce clusters with uniform sizes. In some cases, the true clusters exhibit a known size distribution; in image segmentation, for instance, human-segmented images tend to yield segment sizes that follow a power-law distribution. In this paper, we propose a general framework of power-law graph cut algorithms that produce clusters whose sizes are power-law distributed, and also does not fix the number of clusters upfront. To achieve our goals, we treat the Pitman-Yor exchangeable partition probability function (EPPF) as a regularizer to graph cut objectives. Because the resulting objectives cannot be solved by relaxing via eigenvectors, we derive a simple iterative algorithm to locally optimize the objectives. Moreover, we show that our proposed algorithm can be viewed as performing MAP inference on a particular Pitman-Yor mixture model. Our experiments on various data sets show the effectiveness of our algorithms.
Better Late Than Never: Filling a Void in the History of Fast Matrix Multiplication and Tensor Decompositions
Venue: arXiv cs.NA 2014
Year: 2014

Multilinear and tensor decompositions are a popular tool in linear and multilinear algebra and have a wide range of important applications to modern computing. Our paper of 1972 presented the first nontrivial application of such decompositions to fundamental matrix computations and was also a landmark in the history of the acceleration of matrix multiplication. Published in 1972 in Russian, it has never been translated into English. It has been very rarely cited in the Western literature on matrix multiplication and never in the works on multilinear and tensor decompositions. This motivates us to present its translation into English, together with our brief comments on its impact on the two fields.
Predicting results of the Research Excellence Framework using departmental $h$-Index
Venue: arXiv cs.DL 2014
Year: 2014

We compare estimates for past institutional research performances coming from two bibliometric indicators to the results of the UK's Research Assessment Exercise which last took place in 2008. We demonstrate that a version of the departmental h-index is better correlated with the actual results of that peer-review exercise than a competing metric known as the normalised citation-based indicator. We then determine the corresponding h-indices for 2008-2013, the period examined in the UK's Research Excellence Framework (REF) 2014. We place herewith the resulting predictions on the arXiv in advance of the REF results being published (December 2014). These may be considered as unbiased predictions of relative performances in that exercise. We will revisit this paper after the REF results are available and comment on the reliability or otherwise of these bibliometrics as compared with peer review.
Stacked Quantizers for Compositional Vector Compression
Venue: arXiv cs.CV 2014
Year: 2014

Recently, Babenko and Lempitsky introduced Additive Quantization (AQ), a generalization of Product Quantization (PQ) where a non-independent set of codebooks is used to compress vectors into small binary codes. Unfortunately, under this scheme encoding cannot be done independently in each codebook, and optimal encoding is an NP-hard problem. In this paper, we observe that PQ and AQ are both compositional quantizers that lie on the extremes of the codebook dependence-independence assumption, and explore an intermediate approach that exploits a hierarchical structure in the codebooks. This results in a method that achieves quantization error on par with or lower than AQ, while being several orders of magnitude faster. We perform a complexity analysis of PQ, AQ and our method, and evaluate our approach on standard benchmarks of SIFT and GIST descriptors, as well as on new datasets of features obtained from state-of-the-art convolutional neural networks.